Zobrazeno 1 - 10
of 16 988
pro vyhledávání: '"Shiao AS"'
Autor:
Yan, Yang, Chen, Zhong, Xu, Cai, Shen, Xinglei, Shiao, Jay, Einck, John, Chen, Ronald C, Gao, Hao
Patient-reported outcomes (PROs) directly collected from cancer patients being treated with radiation therapy play a vital role in assisting clinicians in counseling patients regarding likely toxicities. Precise prediction and evaluation of symptoms
Externí odkaz:
http://arxiv.org/abs/2411.10819
Semi-supervised learning (SSL) for medical image segmentation is a challenging yet highly practical task, which reduces reliance on large-scale labeled dataset by leveraging unlabeled samples. Among SSL techniques, the weak-to-strong consistency fram
Externí odkaz:
http://arxiv.org/abs/2410.13486
Autor:
Ma, Qingchuan, Wang, Shiao, Zheng, Tong, Dai, Xiaodong, Wang, Yifeng, Yang, Qingquan, Wang, Xiao
This study addresses the critical challenge of predicting the Q-distribution in long-term stable nuclear fusion task, a key component for advancing clean energy solutions. We introduce an innovative deep learning framework that employs Modern Hopfiel
Externí odkaz:
http://arxiv.org/abs/2410.08889
Autor:
Wang, Shiao, Wang, Yifeng, Ma, Qingchuan, Wang, Xiao, Yan, Ning, Yang, Qingquan, Xu, Guosheng, Tang, Jin
Q-distribution prediction is a crucial research direction in controlled nuclear fusion, with deep learning emerging as a key approach to solving prediction challenges. In this paper, we leverage deep learning techniques to tackle the complexities of
Externí odkaz:
http://arxiv.org/abs/2410.08879
Autor:
Wang, Xiao, Wang, Fuling, Li, Yuehang, Ma, Qingchuan, Wang, Shiao, Jiang, Bo, Li, Chuanfu, Tang, Jin
X-ray image-based medical report generation (MRG) is a pivotal area in artificial intelligence which can significantly reduce diagnostic burdens and patient wait times. Despite significant progress, we believe that the task has reached a bottleneck d
Externí odkaz:
http://arxiv.org/abs/2410.00379
Event camera-based visual tracking has drawn more and more attention in recent years due to the unique imaging principle and advantages of low energy consumption, high dynamic range, and dense temporal resolution. Current event-based tracking algorit
Externí odkaz:
http://arxiv.org/abs/2408.10487
Human Action Recognition (HAR) stands as a pivotal research domain in both computer vision and artificial intelligence, with RGB cameras dominating as the preferred tool for investigation and innovation in this field. However, in real-world applicati
Externí odkaz:
http://arxiv.org/abs/2408.09764
Inspired by the tremendous success of Large Language Models (LLMs), existing X-ray medical report generation methods attempt to leverage large models to achieve better performance. They usually adopt a Transformer to extract the visual features of a
Externí odkaz:
http://arxiv.org/abs/2408.09743
Autor:
Ouyang, Shuyi, Wang, Hongyi, Niu, Ziwei, Bai, Zhenjia, Xie, Shiao, Xu, Yingying, Tong, Ruofeng, Chen, Yen-Wei, Lin, Lanfen
Publikováno v:
Proceedings of the 31st ACM International Conference on Multimedia. 2023: 4768-4777
The task of multi-label image classification involves recognizing multiple objects within a single image. Considering both valuable semantic information contained in the labels and essential visual features presented in the image, tight visual-lingui
Externí odkaz:
http://arxiv.org/abs/2407.16244
Autor:
Wang, Xiao, Kong, Weizhe, Jin, Jiandong, Wang, Shiao, Gao, Ruichong, Ma, Qingchuan, Li, Chenglong, Tang, Jin
Current strong pedestrian attribute recognition models are developed based on Transformer networks, which are computationally heavy. Recently proposed models with linear complexity (e.g., Mamba) have garnered significant attention and have achieved a
Externí odkaz:
http://arxiv.org/abs/2407.10374